• Title/Summary/Keyword: Detection map

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Feature Ranking for Detection of Neuro-degeneration and Vascular Dementia in micro-Raman spectra of Platelet (특징 순위 방법을 이용한 혈소판 라만 스펙트럼에서 퇴행성 뇌신경질환과 혈관성 인지증 분류)

  • Park, Aa-Ron;Baek, Sung-June
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.4
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    • pp.21-26
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    • 2011
  • Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.

Cancer subtype's classifier based on Hybrid Samples Balanced Genetic Algorithm and Extreme Learning Machine (하이브리드 균형 표본 유전 알고리즘과 극한 기계학습에 기반한 암 아류형 분류기)

  • Sachnev, Vasily;Suresh, Sundaram;Choi, Yong Soo
    • Journal of Digital Contents Society
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    • v.17 no.6
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    • pp.565-579
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    • 2016
  • In this paper a novel cancer subtype's classifier based on Hybrid Samples Balanced Genetic Algorithm with Extreme Learning Machine (hSBGA-ELM) is presented. Proposed cancer subtype's classifier uses genes' expression data of 16063 genes from open Global Cancer Map (GCM) data base for accurate cancer subtype's classification. Proposed method efficiently classifies 14 subtypes of cancer (breast, prostate, lung, colorectal, lymphoma, bladder, melanoma, uterus, leukemia, renal, pancreas, ovary, mesothelioma and CNS). Proposed hSBGA-ELM unifies genes' selection procedure and cancer subtype's classification into one framework. Proposed Hybrid Samples Balanced Genetic Algorithm searches a reduced robust set of genes responsible for cancer subtype's classification from 16063 genes available in GCM data base. Selected reduced set of genes is used to build cancer subtype's classifier using Extreme Learning Machine (ELM). As a result, reduced set of robust genes guarantees stable generalization performance of the proposed cancer subtype's classifier. Proposed hSBGA-ELM discovers 95 genes probably responsible for cancer. Comparison with existing cancer subtype's classifiers clear indicates efficiency of the proposed method.

A Study on Establishment of the Levee GIS Database Using LiDAR Data and WAMIS Information (LiDAR 자료와 WAMIS 정보를 활용한 제방 GIS 데이터베이스 구축에 관한 연구)

  • Choing, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.3
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    • pp.104-115
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    • 2014
  • A levee is defined as an man-made structure protecting the areas from temporary flooding. This paper suggests a methodology for establishing the levee GIS database using the airborne topographic LiDAR(Light Detection and Ranging) data taken in the Nakdong river basins and the WAMIS(WAter Management Information System) information. First, the National Levee Database(NLD) established by the USACE(United States Army Corps Engineers) and the levee information tables established by the WAMIS are compared and analyzed. For extracting the levee information from the LiDAR data, the DSM(Digital Surface Model) is generated from the LiDAR point clouds by using the interpolation method. Then, the slope map is generated by calculating the maximum rates of elevation difference between each pixel of the DSM and its neighboring pixels. The slope classification method is employed to extract the levee component polygons such as the levee crown polygons and the levee slope polygons from the slope map. Then, the levee information database is established by integrating the attributes extracted from the identified levee crown and slope polygons with the information provided by the WAMIS. Finally, this paper discusses the advantages and limitations of the levee GIS database established by only using the LiDAR data and suggests a future work for improving the quality of the database.

The Study of Coastal Change Detection Ortho Aerial Photo and Hydrographic Survey: Parcels Submerged (정사항공사진과 해양조사측량을 이용한 해안선변화 탐지에 관한 연구: 포락지 중심으로)

  • Choi Chul Eung;Kim Youn Soo;Suh Yong Cheol
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.17 no.2
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    • pp.61-69
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    • 2005
  • The coastal erosion and the look of a heap which are mainly occurred in the district along the coast are found for various forms such as the estuary closing, the estuary sand bar the development of the coast sand bar, and the modification of coastline. Recently, due to the coastal development, these transformations have been intensified. The change of coast, which has been made slow progress is required long-term study on a searching examination of the root cause and a suggestion of a counter measure. In this research, ortho aerial photos were produced to analyze volumes of topographical alternations that have been progressed fer the long run, by 10s cycle from 1940s through 1990s, to compute accurate volumes of coastline variation, through a datum point and G.C.P (Ground Control Point). Also in this study, without respect to water level, the coastline variation was analyzed by using comparatively analyzed a Idlest land map, a cadastral map. And to analyze topographical variation volumes, the tidal station's materials was used under consideration f3r tide. Finally, topographical variation volumes are comparatively analyzed through surveying and sounding and a point of fine of aviation photographing was calculated and revised. After this research, by using ortho aerial photos, We can understand efficiency of these in computing volumes of variations of coastline by analyzing quantitatively erosion and look of a heap. Besides, in the future, these will be used for information gathering of the coastline integration control system.

Genomics and Molecular Markers for Major Cucurbitaceae Crops (주요 박과작물의 유전체 및 분자마커 연구 현황)

  • Park, Girim;Kim, Nahui;Park, Younghoon
    • Journal of Life Science
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    • v.25 no.9
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    • pp.1059-1071
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    • 2015
  • Watermelon and melon are economically important Cucurbitaceae crops. Recently, the development of molecular markers based on the construction of genetic linkage maps and detection of DNA sequence variants through next generation sequencing are essential as molecular breeding strategies for crop improvement that uses marker-assisted selection and backcrossing. In this paper, we intended to provide useful information for molecular breeding of watermelon and melon by analyzing the current status of international and domestic research efforts on genomics and molecular markers. Due to diverse genetic maps constructed and the reference genome sequencing completed in the past, DNA markers that are useful for selecting important traits including yield, fruit quality, and disease resistances have been reported and publicly available. To date, more than 16 genetic maps and loci and linked markers for more than 40 traits have reported for each watermelon and melon. Furthermore, the functional genes that are responsible for those traits are being continuously discovered by high-density genetic map and map-based cloning. In addition, whole genome resequencing of various germplasm is under progress based on the reference genome. Not only by the efforts for developing novel molecular markers, but application of public marker information currently available will greatly facilitate breeding process through genomics-assisted breeding.

Methodology to Apply Low Spatial Resolution Optical Satellite Images for Large-scale Flood Mapping (대규모 홍수 매핑을 위한 저해상도 광학위성영상의 활용 방법)

  • Piao, Yanyan;Lee, Hwa-Seon;Kim, Kyung-Tak;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.34 no.5
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    • pp.787-799
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    • 2018
  • Accurate and effective mapping is critical step to monitor the spatial distribution and change of flood inundated area in large scale flood event. In this study, we try to suggest methods to use low spatial resolution satellite optical imagery for flood mapping, which has high temporal resolution to cover wide geographical area several times per a day. We selected the Sebou watershed flood in Morocco that was occurred in early 2010, in which several hundred $km^2$ area of the Gharb lowland plain was inundated. MODIS daily surface reflectance product was used to detect the flooded area. The study area showed several distinct spectral patterns within the flooded area, which included pure turbid water and turbid water with vegetation. The flooded area was extracted by thresholding on selected band reflectance and water-related spectral indices. Accuracy of these flooding detection methods were assessed by the reference map obtained from Landsat-5 TM image and qualitative interpretation of the flood map derived. Over 90% of accuracies were obtained for three methods except for the NDWI threshold. Two spectral bands of SWIR and red were essential to detect the flooded area and the simple thresholding on these bands was effective to detect the flooded area. NIR band did not play important role to detect the flooded area while it was useful to separate the water-vegetation mixed flooded classes from the purely water surface.

QTL Scan for Meat Quality Traits Using High-density SNP Chip Analysis in Cross between Korean Native Pig and Yorkshire

  • Kim, S.W.;Li, X.P.;Lee, Y.M.;Choi, Y.I.;Cho, B.W.;Choi, B.H.;Kim, T.H.;Kim, J.J.;Kim, Kwan-Suk
    • Asian-Australasian Journal of Animal Sciences
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    • v.24 no.9
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    • pp.1184-1191
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    • 2011
  • We attempted to generate a linkage map using Illumina Porcine 60K SNP Beadchip genotypes of the $F_2$ offspring from Korean native pig (KNP) crossed with Yorkshire (YS) pig, and to identify quantitative trait loci (QTL) using the line-cross model. Among the genotype information of the 62,136 SNPs obtained from the high-density SNP analysis, 45,308 SNPs were used to select informative markers with allelic frequencies >0.7 between the KNP (n = 16) and YS (n = 8) F0 animals. Of the selected SNP markers, a final set of 500 SNPs with polymorphic information contents (PIC) values of >0.300 in the $F_2$ groups (n = 252) was used for detection of thirty meat quality-related QTL on chromosomes at the 5% significance level and 10 QTL at the 1% significance level. The QTL for crude protein were detected on SSC2, SSC3, SSC6, SSC9 and SSC12; for intramuscular fat and marbling on SSC2, SSC8, SSC12, SSC14 and SSC18; meat color measurements on SSC1, SSC3, SSC4, SSC5, SSC6, SSC10, SSC11, SSC12, SSC16 and SSC18; water content related measurements in pork were detected on SSC4, SSC6, SSC7, SSC10, SSC12 and SSC14. Additional QTL of pork quality traits such as texture, tenderness and pH were detected on SSC6, SSC12, SSC13 and SSC16. The most important chromosomal region of superior pork quality in KNP compared to YS was identified on SSC12. Our results demonstrated that a QTL linkage map of the $F_2$ design in the pig breed can be generated with a selected data set of high density SNP genotypes. The QTL regions detected in this study will provide useful information for identifying genetic factors related to better pork quality in KNP.

Development of Android Smartphone App for Corner Point Feature Extraction using Remote Sensing Image (위성영상정보 기반 코너 포인트 객체 추출 안드로이드 스마트폰 앱 개발)

  • Kang, Sang-Goo;Lee, Ki-Won
    • Korean Journal of Remote Sensing
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    • v.27 no.1
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    • pp.33-41
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    • 2011
  • In the information communication technology, it is world-widely apparent that trend movement from internet web to smartphone app by users demand and developers environment. So it needs kinds of appropriate technological responses from geo-spatial domain regarding this trend. However, most cases in the smartphone app are the map service and location recognition service, and uses of geo-spatial contents are somewhat on the limited level or on the prototype developing stage. In this study, app for extraction of corner point features using geo-spatial imagery and their linkage to database system are developed. Corner extraction is based on Harris algorithm, and all processing modules in database server, application server, and client interface composing app are designed and implemented based on open source. Extracted corner points are applied LOD(Level of Details) process to optimize on display panel. Additional useful function is provided that geo-spatial imagery can be superimposed with the digital map in the same area. It is expected that this app can be utilized to automatic establishment of POI (Point of Interests) or point-based land change detection purposes.

Crop Water Stress Index (CWSI) Mapping for Evaluation of Abnormal Growth of Spring Chinese Cabbage Using Drone-based Thermal Infrared Image (봄배추 생육이상 평가를 위한 드론 열적외 영상 기반 작물 수분 스트레스 지수(CWSI) 분포도 작성)

  • Na, Sang-il;Ahn, Ho-yong;Park, Chan-won;Hong, Suk-young;So, Kyu-ho;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.36 no.5_1
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    • pp.667-677
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    • 2020
  • Crop water stress can be detected based on soil moisture content, crop physiological characteristics and remote-sensing technology. The detection of crop water stress is an important issue for the accurate assessment of yield decline. The crop water stress index (CWSI) has been introduced based on the difference between leaf and air temperature. In this paper, drone-based thermal infrared image was used to map of crop water stress in water control plot (WCP) and water deficit plot (WDP) over spring chinese cabbage fields. The spatial distribution map of CWSI was in strong agreement with the abnormal growth response factors (plant height, plant diameter, and measured value by chlorophyll meter). From these results, CWSI can be used as a good method for evaluation of crop abnormal growth monitoring.

Augmented Reality System using Planar Natural Feature Detection and Its Tracking (동일 평면상의 자연 특징점 검출 및 추적을 이용한 증강현실 시스템)

  • Lee, A-Hyun;Lee, Jae-Young;Lee, Seok-Han;Choi, Jong-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.49-58
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    • 2011
  • Typically, vision-based AR systems operate on the basis of prior knowledge of the environment such as a square marker. The traditional marker-based AR system has a limitation that the marker has to be located in the sensing range. Therefore, there have been considerable research efforts for the techniques known as real-time camera tracking, in which the system attempts to add unknown 3D features to its feature map, and these then provide registration even when the reference map is out of the sensing range. In this paper, we describe a real-time camera tracking framework specifically designed to track a monocular camera in a desktop workspace. Basic idea of the proposed scheme is that a real-time camera tracking is achieved on the basis of a plane tracking algorithm. Also we suggest a method for re-detecting features to maintain registration of virtual objects. The proposed method can cope with the problem that the features cannot be tracked, when they go out of the sensing range. The main advantage of the proposed system are not only low computational cost but also convenient. It can be applicable to an augmented reality system for mobile computing environment.